metadata_check

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the burden, and it does disclose the internal checks performed (known AI tool signatures, unusual metadata patterns, missing camera info, AI-typical resolutions), which is useful. However it never states that the operation is read-only/non-destructive, nor any failure behavior for unreadable or stripped-metadata images, leaving key behavioral traits to inference.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loads the purpose in the first sentence, then lists the detection targets, then the argument. Well ordered with no filler, though the four detection bullets could be tightened into one sentence without losing information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter read-only analysis tool with an output schema present, the definition covers what it does and the one required argument. The remaining gap is the absence of any annotation or statement about safety/read-only behavior and error handling for images lacking metadata.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% and the schema property carries only the title 'Image Path', so the description's Args block is the sole source of meaning — it specifies the path must be absolute. That is a meaningful constraint beyond the schema, though no format/extension examples are given.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (check) and a specific resource (image metadata/EXIF), plus the two things it looks for: AI generation signatures and resolution fingerprints. This inherently distinguishes it from siblings like noise_map, frequency_analysis, and color_analysis, which operate on different image characteristics.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied by the forensic framing (use to detect AI-generated images), but the description never states when this tool is preferable to siblings such as full_forensic_report or error_level_analysis, nor any prerequisites or exclusions. The agent must infer placement in the workflow.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.